Comparing Apples with Oranges

This Friday we will officially launch Trading Consequences this Friday (21st March), with publication of our White Paper and the launch of our visualization and search tools. Ahead of the launch we wanted to give you some idea of what you will be able to access, what you might want to view and what you might want to compare with these new historical research tools. Professor Colin Coates has been exploring the possibilities… 

The “Trading Consequences� website literally allows us to compare apples and oranges.  Both fruits became the objects of substantial international trade in the nineteenth century, as in the right conditions they can remain edible despite being shipped great distances.

Screen shot of a visualisation of Apple Trades

They are complementary fruits in many ways, as apples are grown in temperate climates whilst oranges prefer warmer conditions.  They may overlap geographically, but typically we associate different parts of the world with each fruit.  In the context of the British world, apples grew in the United Kingdom, of course, but they also came from Canada, New Zealand and the United States, among other locations.  Oranges from places like Spain, Florida or Latin America entered the United Kingdom in the nineteenth century.  The two maps which result from entering “apple� and “orange� into the database show, at a glance, how oranges appeared more often in reference to warmer zones than apples.

Screen shot of a visualisation of Orange Trades

The chronological distribution of commodity mentions was roughly similar in both cases.  Increased attention from 1880 to 1900 reflects in part the expansion of the documentation in that period, but it likely also reflected growth in trade and consumption.  Historian James Murton has pointed out that regular trade in apples developed from Canada to Great Britain in the 1880s, focused primarily in Nova Scotia.  On average, one million bushels of apples reached British markets (Murton, 2012).

In contrast, both apples and oranges show sudden spikes in the 1830s, for entirely different reasons.  The spike for apples points the researcher to a useful “Report from the Selection Committee on the Fresh Fruit Trade� in 1839.  But the mid-1830s spike in oranges points instead to the activities of Orange Lodges in Ireland.  The other visualisation shows this anomaly even more clearly, as IRELAND takes on a prominence in related geographical terms in the 1830s that it did not occupy afterwards.

Screenshot of Visualisation looking at trades in the 1830s

This project entailed teaching computers to read as an historian might, and there are distinct advantages to being able to deal with such a wide range of documentation.  However, all historians must be critical of the sources we use. The visualisations in “Trading Consequences� point towards useful sources for further study, and to suggest that historian may wish to consider some regions in their analysis.  The importance of the United States in the discussions about apples is noteworthy, for instance.  Australia has a large number of mentions of oranges, though it is important to note that a small city boasts the same name and could account for part of the number.  (Interestingly enough, Orange, New South Wales, did not grow many oranges according to the Australian Atlas 2006! But it does have apples.)

"Fruit" by Flickr user Garry Knight / garryknight

“Fruit” by Flickr user Garry Knight / garryknight

The increase in mentions of both apples and oranges from the 1880s on may reflect improving living standards in Britain in that period.  Britain’s decision to adopt free trade had led to an increase in a wide variety of imported foodstuffs (Darwin, 2009).  As the heightened attention to both apples and oranges probably shows, these fruits were part of that movement.

The “Trading Consequences� visualisations show some instructive comparisons, some that may point to different ways to conceive of trade in these resources, and others which illustrate the care with which researchers should approach results.

References

  • John Darwin, The Empire Project: The Rise and Fall of the British World-System, 1830-1970 (Cambridge: Cambridge University Press, 2009)
  •  James Murton, “John Bull and Sons: The Empire Marketing Board and the Creation of a British Imperial Food Systemâ€� in Franca Iacovetta et al., eds., Edible Histories, Cultural Politics: Towards a Canadian Food History (Toronto: University of Toronto Press, 2012), 234-35.
  • New South Wales Government, Agriculture – Fruit and Vegetables in the Atlas of New South Wales, Available from: http://www.atlas.nsw.gov.au/public/nsw/home/topic/article/agriculture-fruit-and-vegetables.html

New Infographics Guidelines from the Office for National Statistics and the Magic of Memes

Huge thanks to Tony Hirst (via Peter Burnhill) for flagging up a new set of Infographic Guidelines from the Office for National Statistics. You can read more about the guidelines, and their origins in Matt Juke’s Infographics Superhighway post on the ONS Digital Publishing Blog.

Screen capture from the ONS Infographics Guide

Screen capture from the ONS Infographics Guide (ONS, 2013)

Whilst these guidelines are specifically intended to address the branding needs of the ONS they also address visual storytelling and are a really useful reminder of the importance of conveying clear and useful messages through infographics. Matt Jukes’ post talks about the importance of ensuring that any infographic carrying the ONS logo is credible and uses statistics well. I’d heartily endorse that sentiment for any academic or organisational use of these sorts of visual information, particularly as not all visualisations are created equal.

David McCandless, whose handcrafted visualisation work is highly regarded and tells important stories brilliantly, has received criticism for the accuracy of his depictions. In telling a story it can be hard to represent information as precisely as desired whilst also ensuring the reader knows the key messages, and understands the implications of the data – and of the way the data has been interpreted (the classic example here being the potential bias of map projections for instance). Tools like Textal, Voyant-Tools and visualisations created by City University’s giCentre – and the exciting and highly interactive journal Vectors – are attempting to bridge the gap between beautiful and useful. There are sure to be further initiatives appearing in this direction as the role of visual storytelling becomes better understood and appreciated – and more important in an era of increasingly big data.

I am in the middle of teaching my Social Media module for students on the MSc in Science Communication and Public Engagement at the moment and one of the recurrent themes is the difficulty of getting that balance right between being fun and eye catching and being credible and authoritative.

Infographics and memes (e.g. LOLCATs, the What I think I do/What My Parents Think I do… type images) are a brilliant tool for engaging your audiences if they are done well – analysis of social media sharing and the continued growth of Pinterest confirms that images and video content can make a huge difference to how frequently posts are viewed and shared. However, done poorly they can be misleading and turn off audiences – particularly those that have a longer term relationship with an organisation and value your authoritative status.

One of the things I find fascinating about memes that bubble up – for instance one of the most recent Tumblrs and image memes has been Ryan Gosling Biostatistics (see below) – is the challenging potential they offer. In some ways there could not be a less authoritative or appropriate way to convey information than by creating sharable posters co-opting others’ images but, at the same time,  these are fun mediums and can allow you to juxtapose highly accessible imagery with arcane or inaccessible topics. They are also popular – important if you buy into Henry Jenkins’ “If it doesn’t spread it’s dead” concept – and shows a credibility and understanding of the social media space, for instance the Ryan Gosling Biostatistics meme plays on an already-successful meme, the Ryan Gosling NPR Tumblr.

Screencapture from the Ryan Gosling Biostatistics Tumblr

Screencapture from the Ryan Gosling Biostatistics Tumblr, in this case advertising an American Statistical Society 175th Anniversary event.

The Gosling meme is playful and work well because it relies on the audience’s knowledge and interest in a very specific subject matter. It is also inoffensive unlike some of the popular meme images which relies on racial stereotyping (in imagery and language) for humour. These semi-formal images are perfect for some messages – public health messages can work well in informal spaces for instance, and the Gikii law and technology conference thrives on LOLLamas. But even a great biostatistics meme image is not the sort of imagery appropriate to an organisation as authoritative and formal in it’s brand as the ONS. With social media decisions over the best way to communicate are always a trade off of organisational branding and goals, with your audience/s desires and expectations.

The ONS Infographic guide won’t be right for all organisations/contexts – it is as much about their specific brand guidance as it is about structuring infographics well – but it is a great reminder of the usefulness of guidance, style guides, and of the need to have consistent and accessible organisational approaches to engaging audiences through social media, preferably with strong visual elements.

Useful Links:

Some useful visualisation creation tools:

  • Creately | https://creately.com/ – quick free online flow chart building tool.
  • D3.JShttp://d3js.org/ – for the more code-minded this is a powerful JavaScript library for creating interactive data visualisations.
  • FigShare | http://figshare.com/ – share your research data, including the ability to share and create graphs and visualisations via this innovative site. These are visualisations based on real data so very much fit in with the ONS’ call for quality although you would need to consider how best to turn images and interactives generated into a story for a true infographic.
  • Google Maps | http://maps.google.co.uk/ – Maps are pretty much the original visualisation tool. Tools like EDINA’s own Digimap – and various GIS tools and softwares – enable creation of geospatial visualisations of academic research data, whilst Google Maps offers an accessible option for any map fan to play with. Login, click “My Places”, and “Create Map” or use Google Docs (Insert > Gadget > Add a Gadget > Maps) to create a map.
  • ManyEyes | http://www-958.ibm.com/software/data/cognos/manyeyes/ – a lovely tool for creating visualisations of data that you upload. It takes a while to use well but produces some great visualiations.
  • Prezi | http://prezi.com/ – very engaging flash-based online presentation tool which can also work well for visualisations. Looks great but takes some time to get used to.
  • Textalhttp://www.textal.org/ – like Wordle but designed, by UCL Digital Humanities experts, to enable researchers to create credible visualisations of textual data as well as analysing that text.
  • TimeToast | http://www.timetoast.com/ – create a timeline from your data
  • Simile Widgets | http://www.simile-widgets.org/ – enables you to create a visualisation, timeline or new way to browse your data – you may need to become familiar with some code to use Simile well/successfully.
  • Visual.ly | http://visual.ly/ – free visualisation tools which, whilst mainly used for silly/fun infographics (definitely not ONS appropriate), can be used in more series ways or for informal visualisations and storytelling around your data.
  • Voyant Toolshttp://voyant-tools.org/ – free online interactive visualisations of textual research data. Really useful if your texts are appropriate in terms of IPR and ethics for sharing in this way.
  • Wordle | http://www.wordle.net/ – plugin interview transcripts or other texts for an instant overview of content. Not perfect but a good starting point into data.

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10 things we learned at the Trading Consequences project meeting…

On Thursday 17th and Friday 18th May we held a Trading Consequences project meeting in Edinburgh where the whole team finally got to meet each other after months of virtual meetings. Here are the 10 awesome things we found out…

  1. Visualisation isn’t about pretty pictures it’s about insight. Take for example the  London Underground map and a New York Subway map… you will see some seriously different stylings (you can see both in Aaron’s presentation here). The London Underground Map is all about key points on the routes, the map isn’t a literal representation of distance but a conceptual take on London’s origins as a network of villages. In New York, where residents are used to walking above ground and are particularly used to the grid system for roads the map reflects this in order to make it easier to conceptualise the combination of Subway and walking routes. And that’s the key thing… visualisations are about representing different world views, different conceptions of information, specific mental maps of the data. A good visualisation reflects a particular world view rather than trying to loyally mirror reality.
  2. Image of a banana

    Moved banana by Flickr user ungard | dave ungar

    Yes, we have no bananas! Well, actually, we might have some bananas today but in London in 1905 did you know that you were allowed to steal bananas if they were brown or blackened? There is an oral history description of being allowed to steal these bananas as they couldn’t be sold. So, can we find evidence to back this up? If we are going to then we need to leave as much information in the ontology we are building to ensure we can find and access that sort of detail. Of course we know what we want to look for here – banana-bread ready fruit is a bit of a known unknown – but what about the things we don’t know about yet? The unknown unknowns we may want to find in the future? Not being able to find something in the data we have gathered doesn’t necessarily mean it’s not there, it just means we can’t confirm that it’s there.

  3. The 19th Century take on “animal, vegetable, or mineral?” was “from the sea“, “from the farm“, or “from the forest”?  This is all about ontologies again… So what is an ontology? Well it’s a way to understand the world, a conceptual model that allows you to structure, sort, classify, connect and understand each item within its immediate and wider context. In an era of trading raw materials and early manufactured items “from the sea” made sense, “from the farm” added useful context… similarly we might be used to understanding trees by their genus but historically qualities such as whether it can be sawn or hewn were important classifications. We’ve been thinking about this since the meeting and you can read about some of the issues around ontologies on Ewan’s blog.
  4. Image of artificial eyes

    Eyes (NOT FOR SALE) by Flickr User fumikaharukaze | Fumika Harukaze

    The eyes have it… and that can be a real problem as us humans are quite a lot better built for reading visual information than machines. When we are looking at sources for Trading Consequences we are seeing digitised materials that have been scanned then OCRed (put through Optical Character Recognition). Printing presses used to be pretty quirky – the letter “a” might look squiffy in every print, or a mark might appear on every page, ink may have smudged, etc. Scanning and OCR technology might look much more high tech but they too have quirks – digital cameras and scanners get better all the time and OCR engines improve each year… that means materials we are working with that were digitised years back look noticibly different from those that have been recently scanned and OCRed. That can be pretty challenging… and then we get to the many tables of traded goods. The human may see a very attractive pattern of columns and rows but the computer just doesn’t see it that easily and we have to try to guide it to read the data in so that it makes sense to the machine, to us humans, and that it reflects what was in the original document.

  5. Image of turkey red cotton

    "Turkey red floral patterns." by the National Museum of Scotland's Feastbowl Blog (click through to read a full post on Turkey Red)

    Wild turkey and rubber demands…. Turkey Red is a type of dyed cotton – named after the place not the bird – which was exported in huge amounts, much of it from Aberdeen But Turkey Red was a complicated and expensive die to make and the process was incompatible with the new textile printing processes that were emerging. There was a shift from natural dyes to synthetic materials and demand for Turkey Red plummeted. The project team has been in discussion with Edinburgh University’s Stana Nenadic and her Colouring the Nation project, which specifically looks at the history of Turkey Red. However, this is just one great example of changes in society being echoed by the consequence of trade and we hope this project will help us explore more of these Big changes generally take place at key pivotal dates due to shifts in economic, political and environmental factors and historians will look for these peaks and sharp changes. Changes such a huge increase in demand for rubber because of the bicycle craze!

  6. Lost in translation? With academic historians, informatics researchers, visualisation experts, specialists in geospatially enabled databases and a social media specialist gathered together in one small room with a lot of coffee we knew we’d have to do a lot of talking to explain our very different positions. For a start our informatics researchers are used to beginning with a hypothesis whilst our historical researchers are much more likely to take a grounded research approach. This is a really different way to plan and conduct work and we need to understand where we’re all coming from. The tools this project creates need to enable historians in their processes and we must be careful to build something that meets specific needs and appropriate expectations. At the same time, as a project team, we also need to be working together to ensure our publications schedules make sense so we needed to spend some time getting up to speed on which conferences matter in each discipline, where we can work collaboratively on papers and publications, and what types of research outputs are most important for the project partners.
  7. Image of tape storage.

    The History of Tape Storage by Flickr user Pargon

    Storage solutions: a database is not just “a database”, just like furniture from a certain Swedish home furnishing chain you need to know the measurements, the aesthetic needs, the future extensibility before you buy. And just like a house you need the right foundations to build something stable, fit for purpose and ready to use. What questions we will be asking of our data are the essential starting point here (see also Aaron’s blog, “The question is key in Trading Consequences” ) – knowing these and some sort of suitable ontology early on helps us ensure we can design the right structure for our database.

  8. History in a changeable climate – part of the the Trading Consequences project is to consider the impact, the consequences, of historical trades. That means looking at different resources and seeing what the most likely environmental impacts of timber trade, cattle trade and so on might be. That means users may want to query our data based on those impact – looking up the kind of trades that might contribute to flooding, that may be reflected in famine, that might be affected by draught, etc. That requires a whole separate ontology for environmental impact that can somehow account for these very interconnected factors – and that is a lot harder than it looks!
  9. Image of a lab

    Harvey W. Wiley conducting experiments in his laboratory by DC Public Library Commons | DCPL Commons on Flickr Commons (click for more information)

    Shipping drugs – no, not a sinister diversification for the project but a reflection of the complexity of trading data. We can look for records of trading particular types of medicines and drugs but sometimes that’s not the right data to look at. Botanical trades also reflects the trading of drugs as some plant material was shipped for later use or processing into pharmaceuticals (for an idea of the type of plants involved take a look at the Alnwick Poison Garden). The same issue applies to leather goods for instance – you might trade the hides, specific goods like leather gloves, perhaps even the whole cow. All of those trades may reflect leather trade but understanding, combining and querying that data poses some challenges.

  10. Pithy headings! They matter! Part of our project meeting was considering how we communicate the project. As well as learning to use pithy headings, images, bullet points and other web-friendly formatting, we also found out that blog posts should usually be no more than 200-300 words. We also discussed how people access this site on other devices, particularly mobiles. Although we are working on historical data a lot of us are using smart phones and they have smaller screens and differing requirements. We agreed to apply a new mobile theme – so do try reading this blog on your phone and let us know if you like it!

We hope that gave you a flavour of our kick off meeting. It took place over two days so we’ve obviously trimmed it down a lot but if you have any questions, comments or suggestions do add it here and we’ll get back to you.

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